Figure 1. Time series of surface-derived cloud-base and -top heights and temperatures (1-hour average) and matched MODIS-derived effective cloud heights and temperatures (30-km x 30-km box) for daytime single-layer and overcast stratus clouds over the ACRF SGP site (sample number is ordered from March 2000 to December 2004 for Terra and from July 2002 to December 2004 for Aqua). Error bars denote standard deviations (±1`3;) of MODIS parameters.

Figure 2. This plot shows time series of ARM-derived (1-hour average) and matched Terra MODIS-derived cloud parameters (30-km x 30-km average) for daytime single-layer and overcast stratus clouds over the ACRF SGP site. The good agreement between the surface and MODIS retrieved cloud microphysical properties and high correlations indicate that the temporally averaged surface observations are equivalent to the spatially averaged satellite results. The good agreement also reveals that VISST can provide accurate and reliable retrievals of these parameters for single-layer and overcast stratus clouds.

For reliable application of satellite datasets in cloud processes and climate models, it is important to have a reasonable estimate of the errors in the derived cloud and radiative properties. Ground-based measurements can provide independent "ground-truth" data for estimating uncertainties in satellite-derived cloud properties, but they must first be properly analyzed and validated and their uncertainties must be understood. Comparisons between the ground- and satellite-based observations must be conducted carefully because of significant spatial and temporal differences between the two different observing platforms. Also, because clouds are so variable, a statistically reliable validation requires coincident satellite-surface measurements taken in a variety of conditions. A complete quantitative assessment requires at least 100 independent samples for each of the conditions, and the independent samples must be typically 100-300 km apart and separated by 6 to 12 hours in time for clouds and radiation [Wielicki et al., 2000]. Research funded by the DOE ARM Program compared 5 years of collocated surface-satellite data at the ARM Climate Research Facility (ACRF) Southern Great Plains (SGP) site and found that the Clouds and Earth's Radiant Energy System-moderate-resolution imaging spectroradiometer (CERES-MODIS) effective cloud heights correspond most closely to the physical center of the cloud being, on average, 0.108 + 0.48 km below it. Also, the ARM and MODIS retrieved cloud microphysical properties agree very well with a high level of correlation.

A sensitivity study has shown that a significant portion of the bias is due to the fact that Heff does not correspond to cloud top, but rather to the radiating center of the cloud, which can be at various locations in the clouds due to Liquid water content (LWC) vertical distribution. The remaining bias is caused by using a lapse rate that is not steep enough. Random variations in errors are due to a combination of spatial and temporal sampling differences, uncertainties in the Goddard Earth Observing System (GEOS) surface temperature and the assumed lapse rate. Despite the uncertainties, it concluded that the use of the lapse rate approach can provide a more accurate estimate of boundary-layer cloud-top height than the use of a temperature profile based on radiosonde data or numerical weather analyses. The good agreement between the surface and MODIS retrieved cloud microphysical properties indicate that the uncertainty of spatial-temporal sampling noise is minimized in this study. The re comparison with modest correlation, however, involves both temporal-spatial match and vertical distribution of re.

The results presented here represent only one class of clouds in a single area over a limited range of solar zenith angles. More validation is needed for stratus clouds at different locations, such as polar, desert, and tropical regions, and also for different cloud types, including multilayered and broken clouds. Eventually, enough independent samples will be collected at the available sites to perform statistically significant surface-satellite comparisons for several different climate regimes and cloud types.